Location-aware computing involves the automatic tailoring of information and services based on the current location of the users. A scalable location aware computing system that enables location-based services, as well as the traditional time-aware, user-aware and device-aware services is described in S. Banerjee, et al., “Rover Technology: Enabling Scalable Location-Aware Computing”, MIND Lab, UMIACS-TR 2001 and CS-TR4312, December 2001, pp. 1-14, and S. Banerjee, et al., “Rover: Scalable Location-Aware Computing”, published in “Computer” October 2002, pp. 56-63. The architecture, as presented in the publications, includes the following entities:                End-users—the system maintains a user profile for each end user that defines specific interests of the user and is used to customize the content served;        Client devices through which users interact with the system. The system maintains a device profile for each device, identifying its capabilities and the functionality available at the device;        A wireless access infrastructure which provides wireless connectivity to the clients. Possible wireless access technologies include IEEE802.11 based wireless LANs, Bluetooth and cellular services;        A server system which implements and manages the various services provided to the end users. The servers include the following components:        a controller which provides and manages different services requested by a client. The controller schedules and filters content sent to the clients based on the user and device profiles and their current locations,        a location server which is a dedicated unit responsible for managing the client device location services within the system,        a media streaming unit which provides the streaming of audio and video content to the clients,        a database which stores all content delivered to the clients. The database also serves as a stable store for the state of the users and clients that is maintained by the controller, and        a logger which interacts with all the server components and receives the log messages from their instrumentation modules.        
The database in the system consists of two components including the user info base which maintains user and device information of all active users and devices in the system. It also contains all client specific context of the users and devices, namely profiles and preferences, client location, and triggers defined by the clients. This information changes at a fairly regular rate as a function of client activities, e.g., the client location alters with movements. Another component in the database is the content info base which stores the content that is served by the controller and changes in a less frequent manner. The content provider of the system is responsible for keeping this info base updated.
Although being capable of automatically tailoring information services based on the current location of the user, the described prior art system is somewhat limited in its functionality and is not adaptable to providing the users the capability to send audio/video data streams to entities of interest which may be defined by the user. This includes, for example, logical groups, e.g. multiple users combined by predetermined characteristics, clients and outsiders alike, entities of interest based on their geographic, temporal or functional characteristics, etc. Further, the prior system, as described, does not have a panic alert mechanism for receiving services and/or help from emergency response units, such as police departments or other emergency type units. Additionally, in the prior art system, although the computation is context based, the context only relates to users themselves and does not mitigate other related services. Further, the discussed system does not include an interface which permits authorized data to be seen by an outsider.
Therefore, it would be highly desirable to provide a spatio-temporal-context aware interactive system free of the above-discussed deficiencies of the prior art system, and which would permit a broad range of functionality, such as a panic alert mechanism, recording the audio/video data streams from the client devices on the system's server to be further distributed to an entity defined by the user, and capable of in-real-time dynamical customization of the context structure in response to the dynamics of an interaction session, as well as having the capability of abstracting context related to multiple users and groups.